Syllabus for Applied Pharmaceutical Structural Bioinformatics

Decisions and guidelines

The course is given as a freestanding course. The course is internet-based on part time, access to a computer with internet connection is required. Replaces and equals 3FF700.

Learning outcomes

After completing the course, the student should be able to:

• Explain predictive chemobioinformatic modeling and show how it can be used to solve problems in drug discovery and life sciences.
• Explain the background to and perform and evaluate modeling with supervised and unsupervised machine learning methods.
• Calculate and use chemical descriptors for proteins, peptides and organic molecules using chemobioinformatic tools.
• Perform cluster analysis and explain how they can be used to solve chemobioinformatic problems in the pharmaceutical field.
• Independently be able to build simpler QSAR and proteochemical models, validate and interpret them, and be able to apply the models to solve problems in the life sciences and the pharmaceutical field.

Content

The course teaches how to solve practical problems in pharmacology, life sciences and bioinformatics using free software and databases. The course covers bioinformatics for nucleotide and amino acid sequences and structural bioinformatics. This includes methods, databases and software for analysis and management of amino acid and nucleotide sequences, secondary and tertiary structures of proteins, methods and tools for homology modelling of protein 3D structure, and molecular dynamics simulations and molecular docking. The focus of the course is on practical exercises where you solve problems using your computer. Specifically, the course contains the following sections:

• Introduction to Structural Bioinformatics in the pharmaceutical field.
• Sequence alignments and database searching. Practical exercises in pairwise and multiple sequence alignments, and exercises with sequence databases with applications in the pharmaceutical field.
• Techniques for prediction of secondary protein structure with computational tools and review of the Pfam and PROSITE databases.
• Techniques and methods for prediction of protein 3D structure: Background molecular modelling and energy minimisation. Tools for homology modelling of protein 3D structure and methods for validation of 3D structures.
• Practical exercises with the MODELLER software and structure validation with PROCHECK.
• The physical basis for molecular dynamic simulation. Exercises on molecular dynamic simulations of proteins with GROMACS.
• Molecular docking and drug screening. Tools and applications relating to computer-aided drug design.
• Practical exercises with AutoDock and AutoDock Vina tools.

Instruction

The course is given as a distance course using the Internet and access to a computer with Internet connection is compulsory. The work is done individually through self-study of web-based materials and computer exercises. The reading material is interspersed with interactive questions. Communication between student and teacher takes place via web and email where the student has the opportunity to ask questions. Mandatory elements are assignments handed in via the education portal or email. The course is given in English at half-time (50%) over an 8-weeks period, or at individual pace if teacher resources permit.

Assessment

Written exams take place at the end of the course. For an approved course, in addition to a passing exam, a pass result is required on compulsory parts. Opportunities to supplement unapproved compulsory parts is offered earliest at the next course opportunity. If there are special reasons, the examiner may make exceptions to the specified examination method and allow a student to be examined in another way. Specific reasons may be e.g. need of special educational support verified by the university coordinator.